Systems and methods for associating vehicle operators with driving misses indicated in vehicle operation data

ABSTRACT

Systems and methods for assessing vehicle operation are provided. According to certain aspects, an electronic device may receive and analyze image data depicting an individual located within a vehicle. The electronic device may also access and compile vehicle operation data and operator data corresponding to a state or condition of the vehicle operator. The electronic device may identify, from the vehicle operator data, a set of close misses experienced by the vehicle, correlate the set of close misses with a state or condition of the vehicle operator, and attribute at least some of the close misses to the vehicle operator. A remote server may aggregate and compile corresponding data from a plurality of vehicles.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 15/488,094, filed Apr. 14, 2017, which is continuation of U.S.patent application Ser. No. 14/989,524, now U.S. Pat. No. 9,685,010,filed Jan. 6, 2016. The disclosures of these applications are herebyfully incorporated by reference in their entireties.

FIELD

The present disclosure is directed to detecting and recording parametersassociated with vehicle operation. More particularly, the presentdisclosure is directed to systems and methods for associating vehicleoperators with certain driving events indicated in vehicle operationdata.

BACKGROUND

Individuals have been operating and traveling in vehicles as a means oftransportation for decades. Generally, some drivers exercise more careor caution than do other drivers. In particular, some driversconsistently operate vehicles above the posted speed limit, which mayresult in the drivers having to navigate through or handle obstacleswithin a shorter time window. For example, if a driver is speeding, thedriver may have to swerve more suddenly or turn more sharply than adriver who is obeying the posted speed limit.

Recently, vehicles have experienced an increased prevalence ofelectronic devices and sensors capable of sensing and generating dataassociated with vehicle operation. However, even with this increasingprevalence, there are no existing solutions for determining whenspecific drivers are operating vehicles in certain situations. Forexample, there is no existing solution for determining when a vehicleoperator experiences a “close miss.” Accordingly, there is anopportunity for systems and methods to leverage various data to identifyvehicle operators and record when those vehicle operators experience“close misses.”

SUMMARY

In one aspect, a computer-implemented method in an electronic device ofassessing vehicle operation is provided. The method may includereceiving image data from at least one image sensor located within thevehicle; analyzing, by a computer processor, the image data to identifyan operator of the vehicle; accessing (i) vehicle operation dataassociated with operation of the vehicle, and (ii) operator dataassociated with at least one condition of the operator; and analyzing,by the computer processor, the vehicle operation data and the operatordata, including: identifying, from the vehicle operation data, a set ofclose misses experienced by the vehicle during the operation of thevehicle, correlating the set of close misses to the operator data, andbased on the correlating, attributing at least a portion of the set ofclose misses to the operator. The method may further include recordingan indication of at least the portion of the set of close misses and anidentification of the operator of the vehicle.

In another aspect, a system in an electronic device for assessingvehicle operation is provided. The system may include a memoryconfigured to store non-transitory computer executable instructions, anda processor configured to interface with the memory. The processor maybe configured to execute the non-transitory computer executableinstructions to cause the processor to receive image data from at leastone image sensor located within the vehicle, analyze the image data toidentify an operator of the vehicle, access (i) vehicle operation dataassociated with operation of the vehicle, and (ii) operator dataassociated with at least one condition of the operator, and analyze thevehicle operation data and the operator data, including: identify, fromthe vehicle operation data, a set of close misses experienced by thevehicle during the operation of the vehicle, correlate the set of closemisses to the operator data, and based on the correlating, attribute atleast a portion of the set of close misses to the operator. Theprocessor may further be configured to record an indication of at leastthe portion of the set of close misses and an identification of theoperator of the vehicle.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1A and 1B depict exemplary environments within a vehicle includingvarious components configured to facilitate various functionalities, inaccordance with some embodiments.

FIG. 2 depicts an exemplary signal diagram associated with analyzingdata to identify vehicle operators and close misses, in accordance withsome embodiments.

FIG. 3 depicts an exemplary flow diagram associated with analyzingvehicle operation data to identify close misses, in accordance with someembodiments.

FIGS. 4A and 4B depict exemplary user interfaces associated withgenerating vehicle operation logs, in accordance with some embodiments.

FIG. 5 is a block diagram of an exemplary electronic device, inaccordance with some embodiments.

DETAILED DESCRIPTION

The present embodiments may relate to, inter alia, detecting, recording,and compiling various vehicle operation data. Existing vehicle operationenvironments support the generation of various vehicle operation data.However, there is no way to properly compile the vehicle operation datawith certain associations or pairings in a meaningful manner to enablethe data to be effectively analyzed and used for subsequent applicationsor inspections. The present embodiments improve these shortcomings byeffectively and efficiently organizing the vehicle operation data forsubsequent retrieval and/or analysis.

According to certain aspects, a vehicle or an electronic device withinthe vehicle may be equipped with one or more image sensors. The imagesensor(s) may be configured to capture image data of an operator (or apassenger(s)) of the vehicle and transmit the captured image data to anelectronic device. After receiving the image data, the electronic devicemay access stored user profile data that may include physicalcharacteristics of a set of users. The electronic device may analyze thereceived image data by comparing the received image data to the storeduser profile data to identify an individual depicted in the receivedimage data, where the individual may be an operator of the vehicle.

Further, the electronic device may determine, identify, or accesscertain vehicle operation data, including various sensor data gatheredby one or more sensors of the vehicle as well as sensor data detected byone or more sensors of the electronic device. The electronic device mayalso determine, identify, or access operator data associated with one ormore conditions of an operator of the vehicle. The vehicle operationdata may include or indicate a set of driving events, whereby a drivingevent may be any occurrence of a distinct vehicle movement or maneuver.Some of the driving events may be classified as “close misses” which mayconstitute an occurrence in which the vehicle narrowly avoids or missesan obstacle or an accident. For example, a close miss may be indicatedby a “hard turn,” “a swerve”, or a “hard brake.”

The electronic device may correlate the vehicle operation data with theoperator data to assess potential causes of the close misses. Inparticular, the electronic device may determine whether any identifiedconditions, movements, or the like associated with the operator may havecaused or led to any of the close misses. The electronic device mayaccordingly attribute one or more of the close misses to the vehicleoperator (i.e., the electronic device may deem that the vehicle operatorwas at fault for one or more of the close misses). Additionally, theelectronic device may further store the data by, for example, generatinga vehicle operation log that may indicate the individual and anydetermined close misses.

The systems and methods therefore offer numerous benefits. Inparticular, the individual may review the vehicle operation log toreview or recall certain information, or to analyze certain informationin an attempt to make various improvements (e.g., improve a habit forspeeding). Further, an individual, entity, or the like may access thevehicle operation log for various purposes or applications. For example,an insurance provider may access the vehicle operation log and, based onthe data included in the vehicle operation log, may determine a riskprofile for the vehicle operator according to the determined amount ofclose misses. For further example, a parent may access the vehicleoperation log to monitor vehicle travel by one or more children. Itshould be appreciated that other benefits are envisioned.

The systems and methods discussed herein address a challenge that isparticular to vehicle operation. In particular, the challenge relates toa difficulty in interpreting the multiple types of data associated withoperating vehicles. This is particularly apparent with the increasingamount of vehicle sensors and types of data generated therefrom. Inconventional environments, the data is generated and reviewed withoutany sort of data correlation or log generation. In contrast, the systemsand methods automatically correlate certain types of data as the data isrecorded or generated, which results in effectively compiled data thatmay be used for various applications and interpretations. Therefore,because the systems and methods employ the collection, compiling, andstoring of data associated with vehicle, the systems and methods arenecessarily rooted in computer technology in order to overcome the notedshortcomings that specifically arise in the realm of vehicle operation.

Similarly, the systems and methods provide improvements in a technicalfield, namely, vehicle data compiling. Instead of the systems andmethods merely being performed by hardware components using basicfunctions, the systems and methods employ complex steps that go beyondthe mere concept of simply retrieving and combining data using acomputer. In particular, the hardware components capture image data,analyze the image data in combination with stored user profile data toidentify individual(s) depicted in the image data, access vehicleoperation data and operator data, and analyze the vehicle operation dataand the operator data to determine close misses and correlate the closemisses with the operator data. This combination of elements furtherimpose meaningful limits in that the operations are applied to improvevehicle data compiling by associating multiple types of distinct data ina meaningful and effective way.

According to implementations, the systems and methods may support adynamic, real-time or near-real-time analysis of any captured, received,and/or detected data. In particular, the electronic device may receiveor capture image data in real-time or near real-time, and mayautomatically and dynamically analyze the captured image data bycomparing the captured image data to stored profile data. The electronicdevice may also receive or access certain vehicle operation data andoperator data in real-time or near-real-time, and may automatically anddynamically associate and/or compile the image data, the vehicleoperation data, and the operator data. In this regard, the individualindicated in the data or accessing the data is afforded the benefit ofan accurate and meaningful compilation of data. Further, any individualmay access and analyze the data in real-time or near-real-time toefficiently and effectively facilitate any functionalities orprocessing.

FIG. 1A illustrates an example depiction of an interior of a vehicle 100that may include various components associated with the systems andmethods. In some scenarios, an individual 102 may operate (i.e., drive)the vehicle 100. Although the individual 102 is depicted as sitting inthe driver's seat of the vehicle 100 and operating the vehicle 100, itshould be appreciated that the individual 102 may be a passenger of thevehicle, and may sit in a front passenger seat or any of a set of rearpassenger seats. In scenarios in which the individual 102 is a passengerof the vehicle 100, another individual may operate the vehicle 100.

As depicted in FIG. 1A, the interior of the vehicle 100 may support aset of image sensors 105, 106, 107. In the particular scenario depictedin FIG. 1A, each of the image sensors 105, 107 is located near a topcorner of the interior of the vehicle 100, and the image sensor 106 islocated below a rear view mirror. Although three (3) image sensors aredepicted in FIG. 1A, it should be appreciated that additional or fewerimage sensors are envisioned. Further, it should be appreciated that theimage sensors 105, 106, 107 may be disposed or located at variousalternate or additional portions of the vehicle 100, including on anexterior of the vehicle 100.

Each of the image sensors 105, 106, 107 may be configured to detect andconvey information that constitutes an image. In particular, each of theimage sensors 105, 106, 107 may generate digital image data according tothe detected information, where the digital image data may be in theform of image data and/or video data. Although not depicted in FIG. 1A,the vehicle 100 may also include one or more microphones that may bedisposed in one or more locations, where the microphones may beconfigured to capture audio data that may supplement the digital imagedata captured by the image sensors 105, 106, 107.

The vehicle 100 may also be configured with an electronic device 110configured with any combination of software and hardware components. Insome implementations, the electronic device 110 may be included as partof an on-board diagnostic (OBD) system or any other type of systemconfigured to be installed in the vehicle 100, such as an originalequipment manufacturer (OEM) system. The electronic device 110 mayinclude a set of sensors configured to detect and record varioustelematics data associated with the vehicle 100. In someimplementations, the electronic device 110 may be configured tocommunicate with (i.e., request, retrieve, or receive data from) a setof sensors disposed in other locations of the vehicle 100, such as eachof the image sensors 105, 106, 107. Further, in some implementations,the electronic device 110 itself may be equipped with one or more imagesensors.

According to embodiments, the set of sensors included in the electronicdevice 110 or otherwise configured to communicate with the electronicdevice 110 may be of various types. For example, the set of sensors mayinclude a location module (e.g., a global positioning system (GPS)chip), an accelerometer, an ignition sensor, a clock, speedometer, atorque sensor, a throttle position sensor, a compass, a yaw rate sensor,a tilt sensor, a steering angle sensor, a brake sensor, and/or othersensors. The set of sensors may also be configured to detect variousconditions of the individual 102, including various biometricinformation, movements, and/or the like.

FIG. 1B depicts another configuration of an interior of the vehicle 100that may include various components associated with the systems andmethods. Similar to the depiction of FIG. 1A, the depiction of FIG. 1Billustrates the individual 102 who may be an operator or passenger ofthe vehicle. The individual 102 may access and interface with anelectronic device 115 that may be located within the vehicle 100.Although FIG. 1B depicts the individual 102 holding the electronicdevice 115, it should be appreciated that the electronic device 115 maybe located within the vehicle 100 without the individual 102 contactingthe electronic device 115. For example, the electronic device 115 may besecured within a mount.

According to embodiments, the electronic device 115 may be any type ofelectronic device such as a mobile device (e.g., a smartphone). Itshould be appreciated that other types of electronic devices and/ormobile devices are envisioned, such as notebook computers, tablets,phablets, GPS (Global Positioning System) or GPS-enabled devices, smartwatches, smart glasses, smart bracelets, wearable electronics, PDAs(personal digital assistants), pagers, computing devices configured forwireless communication, and/or the like. The electronic device 115 maybe configured with at least one image sensor 120 configured to capturedigital image data, as discussed herein. The electronic device 115 mayfurther include additional sensors, such as a clock, accelerometer,location module (e.g., GPS chip), gyroscope, compass, biometric, and/orother types of sensors.

In some implementations, the electronic device 115 may be configured tointerface with additional components of the vehicle 100. In particular,the electronic device 115 may interface with the electronic device 110and sensors thereof, any of the image sensors 105, 106, 107, and/orother components of the vehicle 100, such as any additional sensors thatmay be disposed within the vehicle 100. Further, although not depictedin FIG. 1A or 1B, the vehicle 100 and/or each of the electronic devices110, 115 may be equipped with storage or memory capable of storingvarious data.

In operation, either of the electronic devices 110, 115 may beconfigured to receive or otherwise access image data captured by anycombination of the image sensors 105, 106, 107, 120. The electronicdevices 110, 115 may access user profile data that may be stored in thestorage or memory, and may compare the received image data to the userprofile data to identify the individual 102 who may be depicted in theimage data.

The electronic devices 110, 115 may further interface with the varioussensors or other components to assess real-time operation dataassociated with the vehicle 100. For example, the real-time vehicleoperation data may include any sensor data from the yaw rate sensor, thetilt sensor, the steering angle sensor, the brake sensor, and/or anyother sensor. Further, the electronic devices 110, 115 may accesssupplemental movement data from additional sensors, such as the locationmodule, the gyroscope, and/or the accelerometer of the electronic device115. According to embodiments, the real-time vehicle operation dataand/or the supplemental movement data may include or indicate a set ofdriving events corresponding to operation of the vehicle. The electronicdevices 110, 115 may also access operator data from various sensors(including one or more of the image sensors 105, 106, 107), where theoperator data indicates various condition(s) or movement(s) of theindividual 102.

The electronic devices 110, 115 may additionally communicate with remotecomponents via one or more network connections to retrieve additionalinformation related to the environment of the vehicle 100. Inparticular, the electronic devices 110, 115 may retrieve operationparameters specific to a make and model of the vehicle 100. Theelectronic devices 110, 115 may analyze the vehicle operation data, andoptionally the supplemental movement data and/or the operationparameters, to determine an amount of close misses experienced by thevehicle during its operation. According to embodiments, the close missesmay be a subset of the set of driving events included in the real-timeoperation data and/or the supplemental movement data. Further, inembodiments, the electronic devices 110, 115 may determine the closemisses as an occurrence when a certain portion of the gathered datameets or exceeds a predetermined threshold.

The electronic devices 110, 115 may also correlate the identified closemisses with the operator data to determine if certain operatorconditions or movements may have caused or otherwise been a contributingfactor to any of the close misses. Additionally, based on thecorrelation, the electronic devices 110, 115 may attribute any of theclose misses to the individual 102. In particular, the electronicdevices 110, 115 may deem that the individual 102 was at fault or partlyat fault for any of the close misses.

The electronic devices 110, 115 may also generate a vehicle operationlog that may indicate the identified individual and may include any ofthe received or accessed vehicle operation data, where the vehicleoperation log may be later accessed and examined for variousapplications. In a particular embodiment, the electronic devices 110,115 may record instances of any close misses during operation of thevehicle 100 by the individual 102, as well as any details related to theclose misses (e.g., time, location, and type of close miss). Theelectronic devices 110, 115 may also provide, in real-time, nearreal-time, or at another time, the generated vehicle operation log to athird party entity or device (e.g., an insurance provider).

According to embodiments, an individual may manually access and examinethe vehicle operation log, or a computing device may automaticallyaccess and examine the vehicle operation log, to facilitate the variousapplications. For example, an insurance provider may automaticallyanalyze the vehicle operation log to assess the amount of close missesfor which a driver is responsible, and may generate a vehicle insurancepolicy quote accordingly. Accordingly, the insurance provider maygenerate the vehicle insurance policy quote in real-time ornear-real-time to when the electronic device 110, 115 generates thevehicle operation log. Further, the insurance provider may provide thevehicle insurance policy quote to the individual 102, such as when theindividual 102 is still operating the vehicle or otherwise in real-timeor near-real-time to generation of the vehicle operation log, where theindividual 102 may select to purchase the vehicle insurance policy.

FIG. 2 depicts a signal diagram 200 associated with facilitating certainfunctionalities associated with the systems and methods. The signaldiagram 200 includes a set of components that may be associated with avehicle: an image sensor 242 (such as one of the image sensors 105, 106,107, 120 as discussed with respect to FIGS. 1A and 1B), an electronicdevice 246 (such as one of the electronic devices 110, 115 as discussedwith respect to FIGS. 1A and 1B), a set of vehicle sensors 241, and aremote server 243. According to embodiments, the image sensor 242 may bea component of (or separate from) the electronic device 246. Further,according to embodiments, the set of vehicle sensors 241 may include ayaw rate sensor, a tilt sensor, a steering angle sensor, a brake sensor,a location module (e.g., a GPS module), and/or any additional sensorcapable of measuring the movement or general operation of a vehicle.Additionally, the set of vehicle sensors 241 may include sensors capableof measuring operator data including physiological data regarding thevehicle operator such as, for example, a heart rate, heart ratevariability data, a grip pressure, electrodermal activity data, atelematics driving score, a body temperature, an arm movement, a headmovement, a vocal amplitude, a vocal frequency, a vocal pattern, a gazedirection, a gaze duration, a head direction, an eyelid opening, a blinkrate, pupillometry data, a blood pressure, electroencephalographic data,a respiration rate, a respiration pattern, a galvanic skin response,functional near infrared optical brain imaging data, functional magneticresonance imaging data, or electromyographic data.

The signal diagram 200 may begin when the electronic device 246optionally requests (250) image data from the image sensor 242.According to embodiments, the electronic device 246 may automaticallyrequest the image data periodically (e.g., once every ten seconds, onceevery minute, once every hour), or a user of the electronic device 246may cause the electronic device 246 to request the image data. Further,the request may include a specified amount of image data and/or aspecific time component (e.g., real-time image(s), real-time video,image(s) and/or video recorded five minutes ago). It should beappreciated that the image sensor 242 may be internal to or externalfrom the electronic device 246.

The image sensor 242 may send (252) the image data to the electronicdevice 246. In one implementation, the image sensor 242 mayautomatically send the image data to the electronic device 246 inreal-time or near real-time as the image sensor 242 captures the imagedata, and/or in response to a request from the electronic device 246. Inanother implementation, the image sensor 242 may sendpreviously-captured image data to the electronic device 246, such as ifthe image sensor 242 interfaces with some type of memory or storage. Itshould be appreciated that the image data may depict a vehicle operatoror a passenger of the vehicle.

The electronic device 246 may access (254) image profile data associatedwith one or more individuals. In embodiments, the one or moreindividuals may be registered or otherwise associated with the vehicle(e.g., one or more registered drivers of the vehicle). The electronicdevice 246 may access the image profile data from local memory or fromremote storage via a network connection. In one implementation, theelectronic device 246 may access the image profile data from the remoteserver 243. According to embodiments, the image profile data may includea set of attributes, characteristics, and/or the like that may berelated to the one or more individuals. For example, the image profiledata may include facial recognition data related to relative positions,sizes, and/or shapes of the eyes, noses, cheekbones, jaws, and/or otherfeatures of the one or more individuals.

The electronic device 246 may identify (256) an individual depicted inthe image data based on an analysis of the received image data and theaccessed image profile data. According to the embodiments, theindividual depicted in the image data may be the vehicle operator or apassenger of the vehicle, where the electronic device 246 may discernwhether the individual is the vehicle operator or a passenger based on apositioning of the individual as indicated in the image data. In oneimplementation, the electronic device 246 may perform a facialrecognition algorithm or technique using the received image data todetermine that the facial features of an individual depicted in thereceived image data matches those corresponding to an individualincluded in the image profile data. It should be appreciated that othertypes of calculations, algorithms, comparisons, or techniques areenvisioned.

The electronic device 246 may retrieve (258) vehicle operation data fromthe vehicle sensors 241. In particular, the vehicle operation data mayinclude one or more of the following: an angular velocity reading fromthe yaw rate sensor, a pitch and/or roll from the tilt sensor, aposition angle of the steering wheel and a rate of turn from thesteering angle sensor, and/or braking data from the brake sensor. Itshould be appreciated that additional or alternative types of sensordata from various sensors are envisioned (e.g., speed data from aspeedometer). According to embodiments, the electronic device 246 mayautomatically request the vehicle operation data periodically (e.g.,once every ten seconds, once every minute, once every hour), or a userof the electronic device 246 may cause the electronic device 246 torequest the vehicle operation data. Further, the request may include aspecified amount of vehicle operation data and/or a specific timecomponent (e.g., real-time data or data recorded five minutes ago).

In other embodiments, one or more of the vehicle sensors mayautomatically send the corresponding vehicle operation data to theelectronic device 246 in response to a trigger event, such as when thecorresponding sensor data meets or exceeds a threshold amount. Forexample, if the tilt sensor senses a pitch or roll that exceeds athreshold value, then the tilt sensor may provide the pitch and/or rollvalue to the electronic device 246.

The electronic device 246 may optionally access various movement data.In particular, the electronic device 246 may access the movement datafrom various local sensors including a location module, anaccelerometer, a gyroscope, and/or the like. Similar to retrieving thevehicle operation data in (248), the electronic device 246 may request aspecified amount of movement data and/or a specific time component(e.g., real-time data or data recorded five minutes ago). According tosome embodiments, the electronic device 246 may supplement the vehicleoperation data with the movement data.

The electronic device 246 may also retrieve (260) operator data from oneor more of the vehicle sensors 241. In embodiments, the operator datamay include various physiological data regarding the vehicle operatorsuch as, for example, a heart rate, heart rate variability data, a grippressure, electrodermal activity data, a telematics driving score, abody temperature, an arm movement, a head movement, a vocal amplitude, avocal frequency, a vocal pattern, a gaze direction, a gaze duration, ahead direction, an eyelid opening, a blink rate, pupillometry data, ablood pressure, electroencephalographic data, a respiration rate, arespiration pattern, a galvanic skin response, functional near infraredoptical brain imaging data, functional magnetic resonance imaging data,or electromyographic data.

In an optional implementation, the electronic device 246 may retrieve(262) additional or alternative operator data from the image sensor,which may be in the form of additional image data that additionallydepicts the vehicle operator. For example, the additional image data maydepict eye-tracking movements, head-tracking movements, gesture-trackingmovements, operator posture, and/or other visual data that indicatesoperator movements or behaviors. In an embodiment, the electronic device246 may analyze the image data received in (252) to identify theoperator movements or behaviors, in addition to or in lieu of retrievingthe additional image data.

The electronic device 246 may also optionally retrieve (264) certainoperation parameters from the remote server 243 via a network(s). Incertain embodiments, the network(s) may support any type of datacommunication via any standard or technology (e.g., GSM, CDMA, TDMA,WCDMA, LTE, EDGE, OFDM, GPRS, EV-DO, UWB, Internet, IEEE 802 includingEthernet, WiMAX, Wi-Fi, Bluetooth, and others). The network(s) may alsobe one or more private or local networks or dedicated frequency bands.The operation parameters may be certain thresholds or other metrics thatthe electronic device 246 may use to analyze the vehicle operation dataand/or the operator data, where the operation parameters may be based onthe type of vehicle, year of manufacture, condition of the vehicle,and/or other data.

The electronic device 246 may analyze the vehicle operation data toidentify (266) any close misses experienced by the vehicle. In animplementation, the electronic device 246 may further incorporate theoperation parameters retrieved in (264) to analyze the vehicle operationdata. In analyzing the vehicle operation data and optionally theoperation parameters, the electronic device 246 may identify a set ofdriving events included in the data. According to embodiments, the setof driving events may correspond to a set of movements or maneuvers thatthe vehicle undertakes or completes. For example, one of the drivingevents may be a right turn, and another of the driving events may be aninstance of the vehicle braking.

In an implementation, the set of driving events may correspond to thevehicle operation data meeting or exceeding a threshold value. Forexample, one driving event may correspond to the rate of turn from thesteering wheel sensor exceeding a certain value (which may correspond toa swerve). For further example, another driving event may correspond tothe angular velocity reading from the yaw rate sensor exceeding acertain value (which may correspond to a hard turn). Additionally, forexample, another driving event may correspond to the braking data fromthe brake sensor exceeding a certain value coupled with a rapiddeceleration in speed (which may correspond to a hard brake event).

The electronic device 246 may thus identify the close misses from theidentified driving events. According to embodiments, a close miss may bedefined as an instance or occurrence in which the vehicle quickly and/orsuddenly adjusts its operation, which may result in the vehicle narrowlyavoiding or missing an obstacle or an accident. For example, a closemiss may be a strong braking event, a sharp steering event, a hardswerve, a high acceleration, a fast cornering, an excessive swaying, anerratic steering, a driving on the wrong side of the road, and/or othersimilar instance. Further, the amount of close misses may be an absolutenumber of close misses that are associated with the gathered data. Forexample, the electronic device 246 may determine that there are two (2)close misses included in the vehicle operation data resulting from thelast three (3) hours of vehicle operation.

In some embodiments, the close misses may be a portion or all of the setof driving events resulting from the analysis of (266). In particular, adriving event may have a first associated threshold, where a close missmay have a different associated threshold. For example, a “swerve closemiss” may have a higher threshold for the corresponding rate of turndata than does a “swerve driving event.” In other implementations, aclose miss may have the same threshold(s) as a driving event (i.e., anappropriate driving event may effectively be considered a close miss).It should be appreciated that the electronic device 246 may beconfigured with the various threshold values and may incorporatedifferent sensitivities in identifying the set of driving events anddetermining the close misses. In some implementations, the electronicdevice 246 may account for the operation parameters when determining theamount of close misses. For example, the electronic device 246 mayconsider a hard turn having certain operation data a close miss when thevehicle is a minivan, and may not consider a hard turn having the sameoperation data a close miss when the vehicle is a 2-door sports car.

The electronic device 246 may correlate (268) the close misses to theoperator data retrieved in (258) and (262). In an embodiment, theelectronic device 246 may identify an occurrence time of each of theclose misses, for example by examining or accessing time stamp dataassociated with the vehicle operation data. The electronic device 246may then access the operator data for that particular occurrence time,or for immediately prior to the particular occurrence time, to assess astate of the operator. For example, the operator data may indicate thatthe operator glanced away from the road immediately prior to completinga hard swerve event. For further example, the operator data may indicatethat the operator's eyes were sporadically closed in the time leading upto a hard braking event. As an additional example, the operator data mayindicate that the operator was having heart trouble that preceded asporadic lane change. It should be appreciated that additional scenariosare envisioned.

The electronic device 246 may attribute (270) at least a portion of theclose misses to the operator. In particular, the electronic device 246may determine that the operator is at fault for at least the portion ofthe close misses. In an embodiment, the electronic device 246 maydetermine that a certain operator condition or movement occurredimmediately prior to a close miss, and may attribute the close miss tothe operator. The electronic device 246 may perform the attributionaccording to various factors such as the timing and/or degree of theoperator condition or movement, the timing and/or degree of the closemiss, the timing of the operator condition or movement relative to thetiming of the close miss, and/or other factors. For example, theelectronic device 246 may determine that the operator had a high vocalamplitude immediately prior to the vehicle experiencing a hard turn, andmay attribute the hard turn to the operator. For further example, theelectronic device 246 may determine that the operator experiencedsignificant head movement prior to a hard braking event.

The electronic device 246 may record (272) any travel metrics associatedwith operation of the vehicle. In particular, the electronic device 246may record the close misses determined in (266), which close misses areattributed to the vehicle operator, any particular metrics from thevehicle operation data and/or the movement data, timing data, and/orother information. In embodiments, the electronic device 246 may recordthe information in the form of a vehicle operator log or similar recordthat the electronic device 246 may update with new information. Inparticular, the vehicle operation log may include an identification ofthe vehicle operator, a current time and/or a current date, a locationof the vehicle, any information associated with the amount of closemisses and/or the impact thereof (including whether the close misses areattributed to the vehicle operator), and/or any other information.Accordingly, the vehicle operation log may provide an accurate snapshotof operation of the vehicle by the vehicle operator that may be accessedby one or more users or entities. The electronic device 246 may send(274) the travel metrics to the remote server 243, such as via any typeof network connection. Accordingly, a user or administrator associatedwith the remote server 243 may review the travel metrics and facilitateany related functionalities.

According to embodiments, the remote server 243 may aggregate thereceived data from the electronic device 246 and from any otherelectronic device or vehicle. Further, the remote server 243 may analyzethe compiled data to perform further functionalities or assessments. Inparticular, the remote server 243 may determine correlations between andamong certain user conditions or movements, and certain driving eventsor close misses. The remote server 243 may further assess a determine adegree for the correlations. In particular, certain correlations mayhave a stronger correlation than others. The remote server 243 may usethis information to improve vehicle design, identify techniques forreducing or improving certain behaviors or conditions, and facilitateother functionalities that generally improve vehicular safety.

FIG. 3 depicts a block diagram of an exemplary method 300 of assessingvehicle operation data. The method 300 may be facilitated by anelectronic device that may be located within a vehicle or incorporatedas part of the vehicle. The electronic device may support execution of adedicated application that may facilitate the functionalities of themethod 300. Further, the electronic device may enable a user orindividual (e.g., an operator of the vehicle) to make various selectionsand facilitate various functionalities.

The method 300 may begin when the electronic device receives (block 305)image data from at least one image sensor located within the vehicle. Inembodiments, the image sensor may be a component of the electronicdevice itself or may be external to the electronic device. Further, theimage data may be received in real-time or near real-time as the atleast one image sensor captures the image data. After receiving theimage data, the electronic device may access (block 310) image profiledata associated with a set of individuals. In some embodiments, the setof individuals may be registered to or otherwise associated with thevehicle. Further, the image profile data may indicate physicalcharacteristics (e.g., facial features) of the corresponding set ofindividuals.

The electronic device may analyze (block 315) the image data and theimage profile data to identify an operator of the vehicle who isdepicted in the image data. In one implementation, the electronic devicemay perform a facial recognition analysis using the image data and theimage profile data. It should be appreciated that alternate oradditional analyses, techniques, calculations, algorithms, or the likeare envisioned. In some embodiments, the electronic device may not haveenough relevant data to identify the vehicle operator, in which caseprocessing may return to block 305 at which additional image data may bereceived, or processing may end or proceed to other functionality.

The electronic device may further access (block 320) (i) vehicleoperation data associated with operation of the vehicle and (ii)operator data associated with at least one condition of the operator. Inembodiments, the electronic device may access the vehicle operator databy retrieving sensor data from at least one of: a yaw rate sensor, atilt sensor, a steering angle sensor, a location module, and a brakesensor. Further, the electronic device may access the operator data byaccessing at least one of: (i) biometric data associated with theoperator, and (ii) additional image data indicating a movement or aposition of the operator. The biometric data may be in the form of oneor more of: a heart rate, heart rate variability data, a grip pressure,electrodermal activity data, a telematics driving score, a bodytemperature, an arm movement, a head movement, a vocal amplitude, avocal frequency, a vocal pattern, a gaze direction, a gaze duration, ahead direction, an eyelid opening, a blink rate, pupillometry data, ablood pressure, electroencephalographic data, a respiration rate, arespiration pattern, a galvanic skin response, functional near infraredoptical brain imaging data, functional magnetic resonance imaging data,or electromyographic data. Further, the additional image data may beseparate from or included with the image data received in block 305.

The electronic device may analyze the vehicle operation data and theoperator data. In particular, the electronic device identify (block 325)a set of close misses experienced by the vehicle during the operation ofthe vehicle. In embodiments, the electronic device may identify a set ofinstances in which the vehicle operation data exceeds a predeterminedthreshold, where the set of instances may correspond to the set of closemisses. Further, the electronic device may correlate (block 330) the setof close misses to the operator data. In particular, the electronicdevice may identify, for each of the set of close misses, an occurrencetime, and determine a state of the operator immediately prior to each ofthe occurrence times. Moreover, the electronic device may attribute(block 335) at least a portion of the set of close misses to theoperator. In particular, for each of the portion of the set of closemisses, the electronic device may determine that the respective state ofthe operator contributed to the respective close miss.

The electronic device may record (block 340) an indication of theportion of close misses and an identification of the vehicle operator,along with any other vehicle metric data, including a current time, acurrent date, a current location, route information, a time ofoperation, and/or any other data including any data or informationpreviously identified or determined. In embodiments, the electronicdevice may record the data in the form of a vehicle operation log, andmay send the vehicle operation log to a remote server.

FIGS. 4A and 4B illustrate exemplary interfaces associated withassessing vehicle operation using detected or determined vehicleoperation parameters. An electronic device (e.g., a mobile device, suchas a smartphone) may be configured to display the interfaces and/orreceive selections and inputs via the interfaces, where the electronicdevice may be associated with an operator of a vehicle, or may beintegrated into the vehicle. For example, a dedicated application thatis configured to operate on the electronic device may display theinterfaces. It should be appreciated that the interfaces are merelyexemplary and that alternative or additional content is envisioned.

FIG. 4A illustrates an interface 450 associated with the identificationof an individual depicted in image data. The interface 450 may includean information box 451 that identifies the individual (as shown: JohnDoe) and the vehicle (as shown: 2015 SUV). In embodiments, theelectronic device may identify the individual and the vehicle usingimage data received when the individual is operating the vehicle. Theinterface 450 may include a “CANCEL” selection 452 that enables anaccessing user to select to dismiss the interface 450 and a “NEXT”selection 453 that enables an accessing user to select to proceed to asubsequent interface.

FIG. 4B illustrates an additional interface 455 associated with avehicle operation log. In some embodiments, the electronic device maydisplay the additional interface 455 in response to the user selectingthe “NEXT” selection 453. The interface 455 indicates that a vehicle logentry has been created, where the vehicle log entry may include a set ofinformation 456. As illustrated in FIG. 4B, the set of information 456may include a vehicle operator name (as shown: John Doe), the vehicle(as shown: 2015 SUV), a date (as shown: September 1), a time ofoperation (as shown: 08:30-10:02 AM), and an amount of close misses (asshown: 2). It should be appreciated that the interface 455 may includealternate or additional information. For example, the interface 455 mayindicate which of the close misses are attributed to the vehicleoperator. The interface 455 may also include an “OKAY” selection 457that enables the user to select to dismiss the interface 455. Further,the interface 455 may include a “MORE INFO” selection 458 that enablesthe user to view more information, such as more detailed informationassociated with the two (2) identified close misses.

FIG. 5 illustrates a diagram of an exemplary mobile or other electronicdevice 510 (such as one of the electronic devices 110, 115 as discussedwith respect to FIG. 1) in which the functionalities as discussed hereinmay be implemented. It should be appreciated that the electronic device510 may be configured to be transported in a vehicle and/or connect toan on-board telematics platform of the vehicle, as discussed herein.Further, it should be appreciated that the electronic device 510 may beintegrated into an on-board system of the vehicle.

The electronic device 510 may include a processor 522 as well as amemory 578. The memory 578 may store an operating system 579 capable offacilitating the functionalities as discussed herein as well as a set ofapplications 575 (i.e., machine readable instructions). For example, oneof the set of applications 575 may be an image processing application590 configured to analyze image data to identify individuals depicted inthe image data, and a log generation application 591 configured tointerface with sensors and generate vehicle operation logs that mayinclude various vehicle operation parameters. It should be appreciatedthat one or more other applications 592 are envisioned, such as anapplication configured to determine whether a vehicle is traveling intoa direction of the sun.

The processor 522 may interface with the memory 578 to execute theoperating system 579 and the set of applications 575. According to someembodiments, the memory 578 may also include profile data 580 that mayinclude data associated with a set of individuals associated with avehicle. In some implementations, the image processing application 590may interface with the profile data 580 to retrieve appropriate profiledata and compare the profile data to received image data. The memory 578may include one or more forms of volatile and/or non-volatile, fixedand/or removable memory, such as read-only memory (ROM), electronicprogrammable read-only memory (EPROM), random access memory (RAM),erasable electronic programmable read-only memory (EEPROM), and/or otherhard drives, flash memory, MicroSD cards, and others.

The electronic device 510 may further include a communication module 577configured to communicate data via one or more networks 520. Accordingto some embodiments, the communication module 577 may include one ormore transceivers (e.g., WWAN, WLAN, and/or WPAN transceivers)functioning in accordance with IEEE standards, 3GPP standards, or otherstandards, and configured to receive and transmit data via one or moreexternal ports 576. Further, the communication module 577 may include ashort-range network component (e.g., an RFID reader) configured forshort-range network communications. For example, the communicationmodule 577 may receive, via the network 520, image data from a set ofimage sensors. For further example, the communication module 577 maytransmit data to and receive data from a remote server via the network520.

The electronic device 510 may further include a set of sensors 584. Theprocessor 522 and the set of applications 575 may interface with the setof sensors 584 to retrieve and process the corresponding sensor data.The set of sensors 584 may include, for example, a location module, anaccelerometer, a gyroscope, a compass, a weather sensors, one or moreimage sensors, various biometric sensors capable of sensing variousbiometric data as discussed herein, and/or the like. In one particularimplementation, the log generation application 591 may use various datafrom the set of sensors 584 to generate vehicle operation logs.

The electronic device 510 may further include a user interface 581configured to present information to a user and/or receive inputs fromthe user. As shown in FIG. 5, the user interface 581 may include adisplay screen 582 and I/O components 583 (e.g., ports, capacitive orresistive touch sensitive input panels, keys, buttons, lights, LEDs,speakers, microphones). According to some embodiments, the user mayaccess the electronic device 510 via the user interface 581 to reviewinformation and/or perform other functions. In some embodiments, theelectronic device 510 may perform the functionalities as discussedherein as part of a “cloud” network or may otherwise communicate withother hardware or software components within the cloud to send,retrieve, or otherwise analyze data.

In general, a computer program product in accordance with an embodimentmay include a computer usable storage medium (e.g., standard randomaccess memory (RAM), an optical disc, a universal serial bus (USB)drive, or the like) having computer-readable program code embodiedtherein, wherein the computer-readable program code may be adapted to beexecuted by the processor 522 (e.g., working in connection with theoperating system 579) to facilitate the functions as described herein.In this regard, the program code may be implemented in any desiredlanguage, and may be implemented as machine code, assembly code, bytecode, interpretable source code or the like (e.g., via C, C++, Java,Actionscript, Objective-C, Javascript, CSS, XML). In some embodiments,the computer program product may be part of a cloud network ofresources.

Although the following text sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the invention may be defined by the words of the claims setforth at the end of this patent. The detailed description is to beconstrued as exemplary only and does not describe every possibleembodiment, as describing every possible embodiment would beimpractical, if not impossible. One could implement numerous alternateembodiments, using either current technology or technology developedafter the filing date of this patent, which would still fall within thescope of the claims.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (e.g., code embodiedon a non-transitory, machine-readable medium) or hardware. In hardware,the routines, etc., are tangible units capable of performing certainoperations and may be configured or arranged in a certain manner. Inexample embodiments, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware module that operates to perform certain operations asdescribed herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that may be permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that may betemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules may provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it may becommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within a home environment, anoffice environment, or as a server farm), while in other embodiments theprocessors may be distributed across a number of locations.

The performance of certain of the operations may be distributed amongthe one or more processors, not only residing within a single machine,but deployed across a number of machines. In some example embodiments,the one or more processors or processor-implemented modules may belocated in a single geographic location (e.g., within a homeenvironment, an office environment, or a server farm). In other exampleembodiments, the one or more processors or processor-implemented modulesmay be distributed across a number of geographic locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment may be included in at leastone embodiment. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

The terms “insurer,” “insuring party,” and “insurance provider” are usedinterchangeably herein to generally refer to a party or entity (e.g., abusiness or other organizational entity) that provides insuranceproducts, e.g., by offering and issuing insurance policies. Typically,but not necessarily, an insurance provider may be an insurance company.

As used herein, the terms “comprises,” “comprising,” “may include,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the description. Thisdescription, and the claims that follow, should be read to include oneor at least one and the singular also may include the plural unless itis obvious that it is meant otherwise.

This detailed description is to be construed as examples and does notdescribe every possible embodiment, as describing every possibleembodiment would be impractical, if not impossible. One could implementnumerous alternate embodiments, using either current technology ortechnology developed after the filing date of this application.

What is claimed is:
 1. A computer-implemented method in an electronicdevice of assessing operation of a vehicle by an operator, the methodcomprising: accessing (i) vehicle operation data associated with theoperation of the vehicle, and (ii) operator data associated with theoperator, the operator data indicating a set of conditions or movementsof the operator, and comprising image data; analyzing the image data toidentify the operator of the vehicle; identifying, from the vehicleoperation data, a close miss experienced by the vehicle during theoperation of the vehicle; identifying a portion of the operator dataindicating a condition or movement of the operator that occurred priorto an occurrence time of the close miss; and based on the condition ormovement of the operator that occurred prior to the occurrence time ofthe close miss, attributing the close miss to the operator.
 2. Thecomputer-implemented method of claim 1, wherein accessing the vehicleoperation data associated with the operation of the vehicle comprises:retrieving sensor data from at least one of: a yaw rate sensor, a tiltsensor, a steering angle sensor, a location module, and a brake sensor.3. The computer-implemented method of claim 1, wherein accessing theoperator data associated with the operator comprises: accessing (i)biometric data associated with the operator, and (ii) the image dataindicating a movement or a position of the operator.
 4. Thecomputer-implemented method of claim 3, wherein accessing the image datacomprises: accessing the image data from at least one image sensor. 5.The computer-implemented method of claim 1, further comprising:recording an indication of the close miss and an identification of theoperator.
 6. The computer-implemented method of claim 5, furthercomprising: transmitting, to a remote server, the indication of theclose miss and the identification of the operator.
 7. Thecomputer-implemented method of claim 1, wherein identifying, from thevehicle operation data, the close miss experienced by the vehicle duringthe operation of the vehicle comprises: identifying, from the vehicleoperation data, a plurality of close misses experienced by the vehicleduring the operation of the vehicle.
 8. The computer-implemented methodof claim 1, wherein attributing the close miss to the operator isfurther based on an instance in which the vehicle operation data exceedsa predetermined threshold.
 9. The computer-implemented method of claim8, further comprising: accessing the predetermined threshold from aremote server.
 10. A system in an electronic device for assessingoperation of a vehicle by an operator, comprising: a memory configuredto store non-transitory computer executable instructions; and aprocessor configured to interface with the memory, wherein the processoris configured to execute the non-transitory computer executableinstructions to cause the processor to: access (i) vehicle operationdata associated with the operation of the vehicle, and (ii) operatordata associated with the operator, the operator data indicating a set ofconditions or movements of the operator, and comprising image data,analyze the image data to identify the operator of the vehicle,identify, from the vehicle operation data, a close miss experienced bythe vehicle during the operation of the vehicle, identify a portion ofthe operator data indicating a condition or movement of the operatorthat occurred prior to an occurrence time of the close miss, and basedon the condition or movement of the operator that occurred prior to theoccurrence time of the close miss, attribute the close miss to theoperator.
 11. The system of claim 10, wherein to access the vehicleoperation data associated with the operation of the vehicle, theprocessor is configured to: retrieve sensor data from at least one of: ayaw rate sensor, a tilt sensor, a steering angle sensor, a locationmodule, and a brake sensor.
 12. The system of claim 10, wherein toaccess the operator data associated with the operator, the processor isconfigured to: access (i) biometric data associated with the operator,and (ii) the image data indicating a movement or a position of theoperator.
 13. The system of claim 12, wherein to access the image data,the processor is configured to: access the image data from at least oneimage sensor.
 14. The system of claim 10, wherein the processor isconfigured to execute the non-transitory computer executableinstructions to further cause the processor to: record an indication ofthe close miss and an identification of the operator.
 15. The system ofclaim 14, wherein the processor is configured to execute thenon-transitory computer executable instructions to further cause theprocessor to: transmit, to a remote server, the indication of the closemiss and the identification of the operator.
 16. The system of claim 10,wherein to identify, from the vehicle operation data, the close missexperienced by the vehicle during the operation of the vehicle, theprocessor is configured to: identify, from the vehicle operation data, aplurality of close misses experienced by the vehicle during theoperation of the vehicle.
 17. The system of claim 10, wherein theprocessor attributes the close miss to the operator further based on aninstance in which the vehicle operation data exceeds a predeterminedthreshold.
 18. The system of claim 17, wherein the processor isconfigured to execute the non-transitory computer executableinstructions to further cause the processor to: access the predeterminedthreshold from a remote server.